Hungary: Csongrád¶

  • Homepage of project: https://oscovida.github.io
  • Plots are explained at http://oscovida.github.io/plots.html
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In [1]:
import datetime
import time

start = datetime.datetime.now()
print(f"Notebook executed on: {start.strftime('%d/%m/%Y %H:%M:%S%Z')} {time.tzname[time.daylight]}")

Notebook executed on: 07/03/2023 16:41:45 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Hungary", region="Csongrád", weeks=5);
2023-03-07T16:41:49.341188 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 21 Nov 28 Nov 05 Dec 12 Dec 19 Dec 160 160 180 180 200 200 220 220 7-day incidence rate Csongrád, Hungary, last 5 weeks, last data point from 2022-12-21 21 Nov 28 Nov 05 Dec 12 Dec 19 Dec 0 0 50 50 100 100 150 150 200 200 daily change Hungary-Csongrád new cases (rolling 7d mean) Hungary-Csongrád new cases 21 Nov 28 Nov 05 Dec 12 Dec 19 Dec No data available to plot daily change in deaths 21 Nov 28 Nov 05 Dec 12 Dec 19 Dec 0.8 0.8 1.0 1.0 1.2 1.2 R & growth factor (based on cases) Hungary-Csongrád cases daily growth factor Hungary-Csongrád cases daily growth factor (rolling mean) Hungary-Csongrád estimated R (using cases) 21 Nov 28 Nov 05 Dec 12 Dec 19 Dec No data available to plot R & growth factor (based on deaths) 21 Nov 28 Nov 05 Dec 12 Dec 19 Dec 0 0 1000 1000 2000 2000 3000 3000 cases doubling time [days]
In [4]:
overview(country="Hungary", region="Csongrád");
2023-03-07T16:41:54.017417 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 0 2000 2000 4000 4000 7-day incidence rate 229.0 Csongrád, Hungary, last data point from 2022-12-21 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 0 500 500 1000 1000 1500 1500 2000 2000 daily change Hungary-Csongrád new cases (rolling 7d mean) Hungary-Csongrád new cases May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 No data available to plot daily change in deaths May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0.8 0.8 1.0 1.0 1.2 1.2 R & growth factor (based on cases) Hungary-Csongrád cases daily growth factor Hungary-Csongrád cases daily growth factor (rolling mean) Hungary-Csongrád estimated R (using cases) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 No data available to plot R & growth factor (based on deaths) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 0 10000 10000 20000 20000 30000 30000 cases doubling time [days]
In [5]:
compare_plot(country="Hungary", region="Csongrád");

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[5], line 1
----> 1 compare_plot(country="Hungary", region="Csongrád");

File /tank/oscovida/work/oscovida.github.io/oscovida.github.io/.venv/lib/python3.9/site-packages/oscovida/oscovida.py:1976, in compare_plot(country, region, subregion, savefig, normalise, dates, align)
   1974 if normalise:
   1975     _population = population(country=country, region=region, subregion=subregion)
-> 1976     c *= 100000 / _population
   1977     d *= 100000 / _population
   1979 if not subregion and not region:    # i.e. not a region of Germany

TypeError: unsupported operand type(s) for /: 'int' and 'NoneType'
In [6]:
# load the data
cases, deaths = get_region_hungary(county="Csongrád")

# get population of the region for future normalisation:
inhabitants = population(country="Hungary", region="Csongrád")
print(f'Population of country="Hungary", region="Csongrád": {inhabitants} people')

# compose into one table
table = compose_dataframe_summary(cases, deaths)

# show tables with up to 1000 rows
pd.set_option("display.max_rows", 1000)

# display the table
table

Population of country="Hungary", region="Csongrád": None people
Out[6]:
total cases daily new cases
Dátum
2022-12-21 93568 229
2022-12-14 93339 219
2022-12-07 93120 181
2022-11-30 92939 177
2022-11-23 92762 150
2022-11-16 92612 163
2022-11-09 92449 541
2022-10-26 91908 359
2022-10-19 91549 525
2022-10-12 91024 502
2022-10-05 90522 743
2022-09-28 89779 683
2022-09-21 89096 760
2022-09-14 88336 715
2022-09-07 87621 673
2022-08-31 86948 653
2022-08-24 86295 849
2022-08-17 85446 1006
2022-08-10 84440 903
2022-08-03 83537 873
2022-07-27 82664 495
2022-07-20 82169 293
2022-07-13 81876 248
2022-07-06 81628 138
2022-06-29 81490 96
2022-06-22 81394 84
2022-06-15 81310 51
2022-06-08 81259 46
2022-06-01 81213 58
2022-05-25 81155 99
2022-05-18 81056 211
2022-05-11 80845 259
2022-05-02 80586 128
2022-04-28 80458 76
2022-04-27 80382 77
2022-04-26 80305 44
2022-04-25 80261 95
2022-04-22 80166 72
2022-04-21 80094 97
2022-04-20 79997 67
2022-04-19 79930 180
2022-04-14 79750 109
2022-04-13 79641 93
2022-04-12 79548 39
2022-04-11 79509 187
2022-04-08 79322 198
2022-04-06 79124 129
2022-04-05 78995 247
2022-04-01 78748 95
2022-03-31 78653 98
2022-03-30 78555 134
2022-03-29 78421 76
2022-03-28 78345 240
2022-03-25 78105 103
2022-03-24 78002 104
2022-03-23 77898 112
2022-03-22 77786 67
2022-03-21 77719 272
2022-03-18 77447 143
2022-03-17 77304 60
2022-03-16 77244 244
2022-03-11 77000 86
2022-03-10 76914 94
2022-03-09 76820 97
2022-03-08 76723 39
2022-03-07 76684 236
2022-03-04 76448 142
2022-03-03 76306 159
2022-03-02 76147 127
2022-03-01 76020 79
2022-02-28 75941 343
2022-02-25 75598 170
2022-02-24 75428 211
2022-02-23 75217 391
2022-02-22 74826 112
2022-02-21 74714 457
2022-02-18 74257 298
2022-02-17 73959 410
2022-02-16 73549 288
2022-02-15 73261 191
2022-02-14 73070 968
2022-02-11 72102 539
2022-02-10 71563 541
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2022-02-07 70352 1478
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2022-01-31 66328 2100
2022-01-28 64228 739
2022-01-27 63489 766
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2022-01-14 57996 282
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2022-01-07 56896 132
2022-01-06 56764 182
2022-01-05 56582 101
2022-01-04 56481 59
2022-01-03 56422 159
2021-12-31 56263 78
2021-12-30 56185 74
2021-12-29 56111 62
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2021-12-23 55767 111
2021-12-22 55656 73
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2020-05-05 101 0
2020-05-04 101 0
2020-05-03 101 3
2020-05-02 98 1
2020-05-01 97 0
2020-04-30 97 1
2020-04-29 96 7
2020-04-28 89 3
2020-04-27 86 23
2020-04-26 63 0
2020-04-25 63 3
2020-04-24 60 3
2020-04-23 57 0
2020-04-22 57 0
2020-04-21 57 0
2020-04-20 57 0
2020-04-19 57 2
2020-04-18 55 1
2020-04-17 54 2
2020-04-16 52 0
2020-04-15 52 1
2020-04-14 51 4
2020-04-13 47 2
2020-04-12 45 1
2020-04-11 44 2
2020-04-10 42 2
2020-04-09 40 0
2020-04-08 40 8
2020-04-07 32 0
2020-04-06 32 2
2020-04-05 30 5
2020-04-04 25 2
2020-04-03 23 2
2020-04-02 21 4
2020-04-01 17 0

Explore the data in your web browser¶

  • If you want to execute this notebook, click here to use myBinder
  • and wait (~1 to 2 minutes)
  • Then press SHIFT+RETURN to advance code cell to code cell
  • See http://jupyter.org for more details on how to use Jupyter Notebook

Acknowledgements:¶

  • Johns Hopkins University provides data for countries
  • Robert Koch Institute provides data for within Germany
  • Atlo Team for gathering and providing data from Hungary (https://atlo.team/koronamonitor/)
  • Open source and scientific computing community for the data tools
  • Github for hosting repository and html files
  • Project Jupyter for the Notebook and binder service
  • The H2020 project Photon and Neutron Open Science Cloud (PaNOSC)
In [7]:
print(f"Download of data from Johns Hopkins university: cases at {fetch_cases_last_execution()} and "
      f"deaths at {fetch_deaths_last_execution()}.")

Download of data from Johns Hopkins university: cases at 07/03/2023 09:31:22 and deaths at 07/03/2023 09:31:21.
In [8]:
# to force a fresh download of data, run "clear_cache()"
In [9]:
print(f"Notebook execution took: {datetime.datetime.now()-start}")

Notebook execution took: 0:00:10.889295